LRU Cache in Python

A simple implementation of LRU cache in Python for learning purposes.

Data Structures

In this implementation, we use the classic version of the LRU cache which is implemented using a Doubly Linked List and a Hash Map.

We have a custom implementation of Double Linked List.

Doubly Linked List

The API of the Doubly Linked List is as follows:

Name	Description
insert_left	Insert the element in the doubly linked list from the left side.
insert_right	Insert the element in the doubly linked list from the right side.
pop_left	Remove and return the leftmost node in the doubly linked list.
pop_right	Remove and return the rightmost node in the doubly linked list.
delete_node	Delete the node in the doubly linked list.
delete	Delete the first occurrence of the value in the doubly linked list.

LRU Cache

The API of the LRU cache is as follows:

Name	Description
__setitem__	Set the provided value against the provided key in the cache.
__getitem__	Get the value mapped against the provided key if it exists.

Note: __setitem__ and __getitem__ are python data methods for better semantics. Consider them as equal to the set and get methods of any cache.

The working of set and get for this cache is as follows:

1. Set Item

• Takes two arguments -- key and value.
• If cache size is less than maximum cache size allowed
  • Add the value in the doubly linked list from the right side.
  • Map the reference of the doubly linked list node in the hash map against the provided key.
• If cache size is more than maximum cache size allowed
  • Remove the leftmost element from the leftmost element from the doubly linked list.
  • Remove the mapping of that node's value from the hash map.
  • Add the new value in the double linked list from the right side.
  • Map the reference of the doubly linked list node in the hash map against the provided key.

2. Get Item

• Take a single argument -- key.
• If the key does not exist in the hash map, then return None.
• If the key exists
  • Get the doubly linked list node from the hash map for the provided key
  • Delete the node from the doubly linked list.
  • Insert a new node (with same value) into doubly linked list from the right side.
  • Update the hash map for the key with the reference of the new node.